{"id":"https://openalex.org/W4211135365","doi":"https://doi.org/10.3233/jifs-212390","title":"Hand gesture recognition based improved multi-channels CNN architecture using EMG sensors","display_name":"Hand gesture recognition based improved multi-channels CNN architecture using EMG sensors","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4211135365","doi":"https://doi.org/10.3233/jifs-212390"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-212390","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-212390","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100635867","display_name":"Jun Li","orcid":"https://orcid.org/0000-0002-1336-2241"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["College of Electronic and Information Engineering, Hebei University, Baoding, China","College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]},{"raw_affiliation_string":"College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091911365","display_name":"Lixin Wei","orcid":"https://orcid.org/0000-0002-4520-3069"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Wei","raw_affiliation_strings":["College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020982041","display_name":"Yintang Wen","orcid":"https://orcid.org/0009-0001-8909-612X"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yintang Wen","raw_affiliation_strings":["College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100390111","display_name":"Xiaoguang Liu","orcid":"https://orcid.org/0000-0002-0026-3092"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Liu","raw_affiliation_strings":["College of Electronic and Information Engineering, Hebei University, Baoding, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060246595","display_name":"Hongrui Wang","orcid":"https://orcid.org/0000-0001-7194-4728"},"institutions":[{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]},{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongrui Wang","raw_affiliation_strings":["College of Electronic and Information Engineering, Hebei University, Baoding, China","College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, Hebei University, Baoding, China","institution_ids":["https://openalex.org/I43337087"]},{"raw_affiliation_string":"College of Electronic and Information Engineering, Yanshan University, Qinhuangdao, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060246595"],"corresponding_institution_ids":["https://openalex.org/I39333907","https://openalex.org/I43337087"],"apc_list":null,"apc_paid":null,"fwci":0.4803,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.55281548,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"43","issue":"1","first_page":"643","last_page":"656"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7993138432502747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6984905004501343},{"id":"https://openalex.org/keywords/spectrogram","display_name":"Spectrogram","score":0.6808373928070068},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6696039438247681},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6500297784805298},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.6449050307273865},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.6074009537696838},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.5649530291557312},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48659050464630127},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.46212977170944214},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.44439947605133057},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36518627405166626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7993138432502747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6984905004501343},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.6808373928070068},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6696039438247681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6500297784805298},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.6449050307273865},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.6074009537696838},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.5649530291557312},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48659050464630127},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.46212977170944214},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.44439947605133057},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36518627405166626},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-212390","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-212390","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1975419040","https://openalex.org/W2013147447","https://openalex.org/W2027537551","https://openalex.org/W2129069496","https://openalex.org/W2147800946","https://openalex.org/W2165294693","https://openalex.org/W2536497371","https://openalex.org/W2618530766","https://openalex.org/W2684229413","https://openalex.org/W2762706434","https://openalex.org/W2798235612","https://openalex.org/W2809262330","https://openalex.org/W2962975726","https://openalex.org/W2976082972","https://openalex.org/W2982705218","https://openalex.org/W2990030530","https://openalex.org/W2990110246","https://openalex.org/W2990405315","https://openalex.org/W3003233465","https://openalex.org/W3011510996","https://openalex.org/W3011997388","https://openalex.org/W3015638204","https://openalex.org/W3018443015","https://openalex.org/W3025285367","https://openalex.org/W3033127071","https://openalex.org/W3043510495","https://openalex.org/W3047413521","https://openalex.org/W3049551772","https://openalex.org/W3081139476","https://openalex.org/W3081241330","https://openalex.org/W3083834400","https://openalex.org/W3083857326","https://openalex.org/W3099461062","https://openalex.org/W3115844225","https://openalex.org/W3117225812","https://openalex.org/W3131858067","https://openalex.org/W3158189796","https://openalex.org/W3189451737","https://openalex.org/W4235803127","https://openalex.org/W6770619079","https://openalex.org/W6775885025","https://openalex.org/W6777559799","https://openalex.org/W6782811323","https://openalex.org/W6782963101"],"related_works":["https://openalex.org/W2530685530","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W3147379364","https://openalex.org/W2010878661","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735"],"abstract_inverted_index":{"With":[0],"the":[1,44,75,83,86,90,102,116,136,142,146,172,176,184,191,226,239],"continuous":[2],"development":[3],"of":[4,38,78,85,119,138,149,156,190,238],"sensor":[5],"and":[6,30,47,95,162,175,188,197,234],"computer":[7],"technology,":[8],"human-computer":[9,23],"interaction":[10],"technology":[11],"is":[12,82,113,133],"also":[13,215],"improving.":[14],"Gesture":[15],"recognition":[16,41,147,185,208,219],"has":[17,205,216,229],"become":[18],"a":[19,36,127],"research":[20],"hotspot":[21],"in":[22,232],"interaction,":[24],"sign":[25],"language":[26],"recognition,":[27],"rehabilitation":[28],"training,":[29],"sports":[31],"medicine.":[32],"This":[33],"paper":[34],"proposed":[35,192,201,227],"method":[37,202],"hand":[39,69,143],"gestures":[40,70],"which":[42,81,132],"extracts":[43],"time":[45],"domain":[46,49],"frequency":[48],"features":[50,77,118],"from":[51,110],"surface":[52],"electromyography":[53],"(sEMG)":[54],"by":[55,73],"using":[56,74],"an":[57],"improved":[58,129],"multi-channels":[59],"convolutional":[60],"neural":[61],"network":[62],"(IMC-CNN).":[63],"The":[64,166,179,200],"10":[65],"most":[66],"commonly":[67],"used":[68,99,134],"are":[71,98,124,164],"recognized":[72],"spectral":[76],"sEMG":[79,103,107,122],"signals":[80,123],"input":[84,137],"IMC-CNN":[87,139,150,157],"model.":[88],"Firstly,":[89],"third-order":[91],"Butterworth":[92],"low-pass":[93],"filter":[94,97],"high-pass":[96],"to":[100,140],"denoise":[101],"signal.":[104],"Secondly,":[105],"effective":[106],"signal":[108,112],"segment":[109],"denoised":[111],"applied.":[114],"Thirdly,":[115],"spectrogram":[117,130],"different":[120],"channels\u2019":[121],"merged":[125],"into":[126],"comprehensive":[128],"feature":[131],"as":[135],"classify":[141],"gestures.":[144],"Finally,":[145],"accuracy":[148,189,209,220,233],"model,":[151,158],"three":[152],"single":[153],"channel":[154],"CNN":[155],"SVM,":[159],"LDA,":[160],"LCNN":[161],"EMGNET":[163],"compared.":[165],"experiment":[167],"was":[168],"carried":[169],"out":[170],"on":[171,210,221],"same":[173,177],"dataset":[174],"computer.":[178],"experimental":[180],"results":[181],"showed":[182],"that":[183,237],"accuracy,":[186],"sensitivity":[187],"model":[193,228],"reached":[194],"97.5%,":[195],"97.25%":[196],"96.25%":[198],"respectively.":[199],"not":[203],"only":[204],"high":[206,217],"average":[207,218],"MYO":[211],"collected":[212],"dataset,":[213],"but":[214],"NinaPro":[222],"DB5":[223],"dataset.":[224],"Overall,":[225],"more":[230],"advantages":[231],"efficiency":[235],"than":[236],"comparison":[240],"models.":[241]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
